Latest version

We enter to 2018 with a new perClass 5.2 release. It brings interactive confusion matrix that significantly simplifies tuning multi-class classifiers and exploring their performance capabilities. There is also support for C-weighting in SVM which allows us to explicitly fix importance of certain classes and significantly faster training of RBF networks scalable to very large problems. Happy new year 2018 to everyone!

Happy to announce perClass 5 with support for deep convolutional networks! The new sddeepnet command allows you to design architecture and train a deep network in one step. A GUI with training progress is available so that network behaviour can be understood and architecture improved. Other improvements include image feature extraction and upgrade to SVM optimizer.

Happy to announce availability of perClass 4.8 that brings support for zooming in image figures (also with a convenient keyboard +/- shortcuts, that do not need mode change), new image feature extractors (orientation histograms and gray-level morphology) and more! More information in Release notes. Enjoy!

4.6 release brings significantly simpler setting of a current op.point on ROC characteristic with a combination of a constrain and performance maximization. New enhancement is a support for direct classifier execution on uint8 or uint16 buffers (think applying classifiers to raw image buffers without content casting - very cool!). There are also several new convolutional filter banks for local image feature extraction and multiple fixes. More information in Release notes. Enjoy!